A Novel Quantum-Behaved Particle Swarm Algorithm and Its Application

Aiming to the similar Dynamic and Multi-objective Optimization Problem such as Collision Detection (CD), where as many of the collision pairs satisfying the collision conditions can be detected in certain time interval, notices that the detected collision pairs are not necessarily the globally optimal solution. A novel Quantum-Behaved Particle Swarm Algorithm (QPSO) was proposed. For this problem, the iteration searching process of quantum-behaved particle has been changed, in this algorithm, once a new position satisfying the condition is detected, then the next searching will be converge towards the latest detected position which maybe not the globally or locally optimal solution. This strategy significantly improved the searching ability for the satisfied position in a limited time interval. The new QPSO apply to CD shows that the efficiency is much better than the traditional QPSO.